- ml:机器学习算法模块,包含一些视觉中最常用的传统机器学习算法。 - flann:最近邻算法库,Fast Library for Approximate Nearest Neighbors,用于在多维空间进行聚类和检索,经常和关键点匹配搭配使用。 - gpu:包含了一些gpu加速的接口,底层的加速是CUDA实现。 - photo:计算摄像学(Computational Photography)相关的接口,当...
Augmentor is an image augmentation library in Python for machine learning. It aims to make image augmentation platform and framework independent, more convenient, less error prone, and reproducible. It employs a stochastic approach using building blocks that allow for operations to be pieced together ...
A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and partially multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle ...
AugLy, by Facebook Research (now Meta Research) is a data augmentation library that supports over 100 types of augmentations in audio, images, text, and video. The augmentations can be configured with metadata, and composed to achieve the effects you want. ...
Bio-Volumentations: A Python library for augmentation of volumetric image sequencesData augmentation is a widely used technique to increase generalization ability of deep learning models, especially when dealing with sparse training data. It is also crucial in biomedical applications, where annotated ...
X,Y=get_next_sample()fortintransform:# data augmentationX,Y=t(X,Y)pred=model.predict(X,Y) 现在,我们可以深入研究本文的目的,并查看图像增广技术。 旋转 第一个,也是最简单的一个,包括在图像的水平和垂直轴上随机执行翻转。换句话说,执行垂直翻转的机会为50/100,执行水平翻转的机会为50/100。
- 图片数据增加(data augmentation)的小工具 -物体检测框标注小工具 其中后两个例子的代码可以在下面地址直接下载: 6.1 OpenCV简介 OpenCV是计算机视觉领域应用最广泛的开源工具包,基于C/C++,支持Linux/Windows/MacOS/Android/iOS,并提供了Python,Matlab和Java等语言的接口,因为其丰富的接口,优秀的性能和商业友好的使用...
10.2 NLPAug Library 10.3 Things to keep in mind 1. Easy Data Augmentation(EDA) EDA是一种简单但非常有效的方法,具体包括随机替换,随机插入,随机交换,随机删除等。 代码也很简单:EDA code 2. An Easier Data Augmentation(AEDA) AEDA方法很简单,就是在句子中间添加标点符号以此来增强数据。整篇文章正文只有一...
OpenCV (i.e. cv2 must be available in python). The library is mainly tested in OpenCV 2, but seems to also work in OpenCV 3. pip install git+https://github.com/aleju/imgaug 或者 pipinstallimgaug 前者安装github最新版本,后者安装pypi版本。
目标检测支持许多视觉任务,如实例分割、姿态估计、跟踪和动作识别,这些计算机视觉任务在监控、自动驾驶和视觉答疑等领域有着广泛的应用。随着这种广泛的实际应用,目标检测自然成为一个活跃的研究领域。 我们在Fynd的研究团队一直在训练一个行人检测模型来支持我们的目标跟踪模型。在本文中,我们将介绍如何选择一个模型架构,...